Who We AreBuilding the AI-first frontier enterprise.

We are a integral technology consultancy with a trademarked, AI-first approach

We are small enough to care locally, big enough to deliver globally (10 countries, 450+ experts from 50+ nationalities)

We are becoming an agentic organization, adopting the AI-native operating model we bring to our clients.

We are robust and resilient (100% independent, 0 debt, founded 2009)

We are AI-native professionals who invest in what we believe and work as a collective intelligence

We are positive, courageous and deliver at the leading edge.

Who We AreBuilding the AI-first frontier enterprise.We are a global technology consultancy with a trademarked, AI-first approach —Gen-e2.

It redefines how enterprises build digital products and transform their organizations with AI.

We do the right thing, and we do it right.

We're proud to be a World Economic Forum New Champion, and a B Corp-certified company.

We are small enough to care locally, big enough to deliver globally (10 countries, 450+ experts from 50+ nationalities)

We are becoming an agentic organization, adopting the AI-native operating model we bring to our clients.

We are robust and resilient ( 100% independent, 0 debt, founded 2009)

We are AI-native professionals who invest in what we believe and work as a collective intelligence

We are positive, courageous and deliver at the leading edge.

Your RoleAs a

Data Engineer

for a leading insurance company, you will play a key role in building a data-driven decision-making culture. You will design resilient and secure solutions that transform raw data into strategic insights for underwriting, risk management, fraud prevention, and customer experience.

Design, build,



and maintain scalable and secure data pipelines in cloud environments (AWS, GCP, or Azure).

Integrate large volumes of structured and unstructured data from core insurance systems (such as policies, claims, CRM, ERP).

Automate data ingestion, transformation, and quality processes using tools such as Apache Spark, dbt, Kafka, and Airflow.

Build and maintain modern data lakes and warehouses (Snowflake, BigQuery, Redshift).

Implement data quality, lineage, and governance validations (Great Expectations, Deequ, OpenMetadata).

Ensure compliance with data regulations (GDPR, SOC2, etc.) and internal security policies.Design optimized datasets to enable machine learning models, predictive analytics, and dashboards (Power BI, Looker, Tableau).

Collaborate with data scientists, architects, and business stakeholders to democratize access to trusted data.

Document data architectures, pipelines, transformation standards, and lineage.

Who You Are

Experience with modern data processing frameworks: Spark, databricks, dbt, Kafka, Apache Beam.

Strong command of Python and advanced SQL.

Hands-on experience with Azure cloud platforms (Data Factory, Synapse).

Knowledge of modern Data Lake / Data Warehouse design (Snowflake, Redshift, BigQuery).

Familiarity with DataOps, testing, and CI/CD practices in data pipelines.

Experience with workflow orchestration systems such as Airflow or Dagster.

Understanding of data quality and governance frameworks:



Great Expectations, Deequ, DataHub, OpenLineage.

Knowledge of streaming technologies: Kafka, Pub/Sub, Kinesis.

Upper-intermediate English level (B2 or higher) for global collaboration.

Nice to Have

Familiarity with event-driven architectures and microservices.

Previous experience in the financial or insurance sector.

Certifications such as Azure Data Engineer or Fabric Data Engineer.

Experience with MLOps solutions (Vertex AI, SageMaker, MLFlow).

AI-Native Engineering (Core Expectation)

Use Generative AI coding tools (e.g., GitHub Copilot, Cursor) as a first-class engineering assistant for:

Code scaffolding and refactoring

Code generation and optimisation

Test-cases and documentation generation

Build applications through AI-driven development practices, including:

AI-assisted debugging and troubleshooting

Intelligent code completion and pattern recognition

Automated documentation generation

Apply prompt engineering best practices for reliable, repeatable engineering outcomes.

Validate GenAI output (determinism checks, guardrails, fallback logic).

More About PALO ITOur clients include some of the world’s most successful companies. We collaborate with leading enterprises, next-generation businesses and frontier partners, shaping what comes next, helping them scale AI and solve complex business and technology challenges.

What We Offer

Stimulating working environments

Unique career path

International mobility

Internal R&D; projects (including Gen-e2)

Knowledge sharing

Personalized training via PALO IT Academy

Entrepreneurship & intrapreneurship

For more on our team culture and benefits, check out our careers page.

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📌 AI Native Data Engineer (Ciudad de México)
🏢 Palo It
📍 Ciudad de México